Fragment Database Analysis Using Molecular Shape Fingerprints

John D. MacCuish Norah E. MacCuish,

Michael Hawrylycz, and Mitch Chapman

ACS San Francisco 2010 CINF

john.maccuish@mesaac.com

•Shape Fingerprints: quasi-Monte Carlo integration approach

•2D substructure commonality

•3D shape and pharmacophore features analogue

•Fragment Database Example

•Future Work

Outline

quasi-Monte Carlo Integration (QMC)*

•Approximate a 3D volume -- e.g., CPK van der Waals

•In practice, quasi-randomly generated points have best error convergence in low dimensions.

•Align volumes using binomial sampling = shape fingerprints, and SVD

•Fast and accurate*”Quasi-Monte Carlo integration for the fast and effective generation of molecular shape fingerprints”, ACS San Francisco, Wednesday 2:30 , COMP 346

Binomial Sampling

Four subfingerprintsFind maximumalignment to otherfingerprints of confirmationssimilarly sampled

Maximum Tanimotofor best alignment

2D Substructure Commonality

• Exploratory visualization tool on a series or a 2D cluster of structures.

• Akin to loosening the constraint on a maximal common substructure (MCS).

• Path based 2D fingerprint form: “Stigmata”*

• Key-based 2D fingerprint form “ChemTattoo”

*"Stigmata: An Algorithm To Determine Structural Commonalities in Diverse Datasets", Shemetulskis, et al, JCIM, 36(4),1996, pp. 862-871

2D Substructure Commonality2D 768 Key-based Fingerprint

"Substructure commonality analysis and visualization with new key-based binary fingerprinter", Norah MacCuish, ACS Chicago, CINF Session, March 24-28, 2007.

2D ChemTattoo• Generate the modal fingerprint from the input data set

• Modal fingerprint is the same length as the input data set 2D fingerprints

• A bit is set in the Modal if that ‘key’ occurs at least in the threshold number of input molecules

• Compare each input 2D fingerprint against the Modal Fingerprint

• Calculate atom score (counts) for each atom for each input structure that reflects the number of modal keys that a given atom participates in. Color code the scores and depict the 2D structures.

2D ChemTattoo

Four 2D fingerprintsThreshold set to 1.0 -- no bit in common among all 4 fingerprints

Threshold set to 0.5 -- some bits in common among all 4 fingerprints

2D ChemTattoo

PUT CHEMVC EX OUTPUT HERE

Pharmacophore Extension

• Adding a pharmacophore extension to quasi-Monte Carlo generated shape fingerprints.

• Substructure matching with pharmacophore features with user defined SMARTS

• Create a ChemTattoo analogue in 3D, map the features onto the shape fingerprint.

• Apply to 3D shape clusters, similarity searching, etc.

ChemTattoo 3D• Allow the pharmacophore features to included standard

definitions (HBond donor, HBond acceptor, etc. Or allow a user defined set of definitions -- SMARTS based)

• Perform shape fingerprint clustering and analyze the resulting clusters to perceive patterns (modal) in the pharmacophore feature space

• Use a known target as the modal and query a database to find similar shape (based on shape fingerprints) and align the shape hits based on the pharmacophore features of the target.

• Apply these ideas to fragments to find potential bioisosteres for an active fragment found from a fragment screen

Fragment Database• ZINC Fragment database, ~500K

compounds

• Cluster in 2D using 768 MACCS Keys Fingerprints

• Select the Representatives to create a 2D diverse set

• Generate multi-conformations (< 5Kcals) and Shape Fingerprints for all conformers

• Shape Fragment Database contains: 3,265 structures, 24,029 conformers

Bacterial 23S rRNA Fragment Screen1. Generate conformers for the active fragment2. Search Fragment Database w/ Shape FP cutoff:

0.6 - 324 conformers share the same shape3. Identify the Pharmacophore Features in Target

(features can be user defined)4. Score the Fragment 3D database based on the

number of modal pharmacophore features for fragments within the shape cutoff (require at least two pharmacophore matches)

5. Display the highlighted pharmacophore features in the target with a surface overlay

6. Align the hits via shape -- slider bars display shape matches that also have matching features within the slider bar distance

Kd > 100µMMS

Nature Reviews Drug Discovery v.3 8/04, p. 669

Bacterial 23S rRNA

•Pharmacophore features of Active fragment•Shape of Active fragment w/ features

highlighted•Hitlist of one conformation of Active

fragment with highest scoring matches•Shapes aligned for the best shape

fingerprint score

Bacterial 23S rRNAShowing hitlist...

User to move the slider bar on the ‘red’ HBond Acceptor and find the shape matched fragment that also has a HBond Acceptor ‘close’ in distance space to the target.

Future Work• Adding in Thresholding

• More experiments in industrial settings

• Expanding the pharmacophore default feature definitions

• Better visualization tools

Acknowledgments• Open Source

• JMol

• Balloon

• OpenBabel

• BKChem

• Mesa Software

• ChemTattoo 2D, 3D

• Shape Fingerprint Module

• Fingerprint Module 2D

• Parallel Grouping Module

• WebflowDD

• Databases

• ZINC

• PDB

john.maccuish@mesaac.com